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• Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
  2025
• Trading Off Privacy, Utility and Efficiency in Federated Learning
  2022
• A Game-theoretic Framework for Privacy-preserving Federated Learning
  2023
• Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion
  2023
• Theoretically Principled Federated Learning for Balancing Privacy and Utility
  2023
• Privacy in Large Language Models: Attacks, Defenses and Future Directions
  2023
• Bridging Privacy and Robustness for Trustworthy Machine Learning
  2024
• No Free Lunch Theorem for Privacy-Preserving LLM Inference
  2024
• Fed-AugMix: Balancing Privacy and Utility via Data Augmentation
  2024